Land subsidence is a common geological hazard. Rapid urban expansion has led to different degrees of ground subsidence within Wuhan in the past few years. The novel coronavirus outbreak in 2020 has seriously impacted urban construction and people’s lives in Wuhan. Land subsidence in Wuhan has changed greatly with the resumption of work and production. We used 80 Sentinel-1A Synthetic Aperture Radar (SAR) images covering Wuhan to obtain the land subsidence change information of Wuhan from July 2017 to September 2021 by using the small baseline subset interferometric SAR technique. Results show that the subsidence in Wuhan is uneven and concentrated in a few areas, and the maximum subsidence rate reached 57 mm/yr during the study period. Compared with land deformation before 2017, the land subsidence in Wuhan is more obvious after 2020. The most severe area of subsidence is located near Qingling in Hongshan District, with a maximum accumulated subsidence of 90 mm, and obvious subsidence funnels are observed in Qiaokou, Jiangan, Wuchang and Qingshan Districts. The location of subsidence centers in Wuhan is associated with building intensity, and most of the subsidence funnels are formed in connection with urban subway construction and building construction. Carbonate belt and soft ground cover areas are more likely to lead to karst collapse and land subsidence phenomena. Seasonal changes are observed in the land subsidence in Wuhan. A large amount of rainfall can replenish groundwater resources and reduce the rate of land subsidence. The change in water level in the Yangtze River has a certain impact on the land subsidence along the rivers in Wuhan, but the overall impact is small. An obvious uplift is observed in Caidian District in the south of Wuhan, and the reason may be related to the physical and chemical expansion effects of the expansive clay.

Safety assessment must accurately grasp deformation information of a high-speed railway bridge. When the ground-based radar collected high-frequency data, white and colored noises will be present in the radar signal due to the influence of environment and instrument errors. The existence of the above-mentioned two kinds of noises will affect the accurate estimation of deformation information. Based on the above situation, a ground-based real aperture radar (GB-RAR) deformation information estimation method considering the effect of colored noise was proposed in this work. The proposed method was applied to the safety monitoring and analysis of East Lake High-tech Bridge during the Wuhan Metro Line 11 shield tunnel crossing underneath this bridge. First, the settlement deformation time series of the bridge was derived based on GB-RAR, and it was verified by leveling at an accuracy better than 0.27 mm. Second, white, and colored noises were detected in the denoised settlement deformation time series through a power spectral analysis and maximum likelihood estimation, and the colored noise spectral indexes were approximately −1. Finally, according to the proposed method, the estimated settlement rates of No. 7 and 8 piers were 0.0112 ± 0.0026 and −0.0046 ± 0.0053 mm/h, and the accumulative settlement values were −0.40 and −0.16 mm, respectively. The results were in good agreement with the results of leveling measurement and more accurate than those of the deformation information estimation method without considering the effect of colored noise. The research results showed the reliability and effectiveness of the method in this work, and the bridge was stable and safe during the monitoring period.

Bridges play a crucial role in the development of the national economy and transportation industry, and their deformation monitoring is vital for ensuring their health. Therefore, it is necessary to conduct long-term monitoring of bridges’ deformation. This study monitored the deformation of the Wuhan Yangtze River Bridge using the SBAS-InSAR technology and Sentinel-1A data. The deformation results were analyzed in combination with bridge structure, human activity, temperature and stratigraphy. The results were as follows: (1) The vertical deformation rate of the bridge was between −15.6 and 10.7 mm/year, and part of the deformation belonged to rebound deformation; (2) The middle span deformation is the largest and the uplift and lowering alternate; (3) The reduction in human activity is the reason for the lower deformation amplitude from January to October 2020 compared to after October 2020; (4) A positive correlation between deformation and temperature was observed only along a portion of the bridge; (5) There is no direct correlation between observed lowering and stratigraphy under the bridge piers, as the sinking is presumably absorbed by the bridge structure.

Due to extensive soft soil and high human activities, Wuhan is a hotspot for land subsidence. This study used the time-series InSAR to calculate the spatial and temporal distribution map of subsidence in Wuhan and analyze the causes of subsidence. An improved fuzzy analytic hierarchy process (GD-FAHP) was proposed and integrated with the Entropy Weight Method (EWM) to assess the hazard and vulnerability of land subsidence using multiple evaluation factors, thereby deriving the spatial distribution characteristics of subsidence risk in Wuhan. Results indicated the following: (1) Maximum subsidence rates reached −49 mm/a, with the most severe deformation localized in Hongshan District, exhibiting a cumulative displacement of −135 mm. Comparative validation between InSAR results and leveling was conducted, demonstrating the reliability of InSAR monitoring. (2) Areas with frequent urban construction largely coincided with subsidence locations. In addition, the analysis indicated that rainfall and hydrogeological conditions were also correlated with land subsidence. (3) The proposed risk assessment model effectively identified high-risk areas concentrated in central urban zones, particularly the Hongshan and Wuchang Districts. This research establishes a methodological framework for urban hazard mitigation and provides actionable insights for subsidence risk reduction strategies.